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Prediction of vertical jump height from anthropometric factors in male and female martial arts athletes

Abidin NZ, Adam MB

Malays J Med Sci, 2013 Jan;20(1):39-45.
PMID: 23785254 MyJurnal

BACKGROUND: Vertical jump is an index representing leg/kick power. The explosive movement of the kick is the key to scoring in martial arts competitions. It is important to determine factors that influence the vertical jump to help athletes improve their leg power. The objective of the present study is to identify anthropometric factors that influence vertical jump height for male and female martial arts athletes.
METHODS: Twenty-nine male and 25 female athletes participated in this study. Participants were Malaysian undergraduate students whose ages ranged from 18 to 24 years old. Their heights were measured using a stadiometer. The subjects were weighted using digital scale. Body mass index was calculated by kg/m(2). Waist-hip ratio was measured from the ratio of waist to hip circumferences. Body fat % was obtained from the sum of four skinfold thickness using Harpenden callipers. The highest vertical jump from a stationary standing position was recorded. The maximum grip was recorded using a dynamometer. For standing back strength, the maximum pull upwards using a handle bar was recorded. Multiple linear regression was used to obtain the relationship between vertical jump height and explanatory variables with gender effect.
RESULTS: Body fat % has a significant negative relationship with vertical jump height (P < 0.001). The effect of gender is significant (P < 0.001): on average, males jumped 26% higher than females did.
CONCLUSION: Vertical jump height of martial arts athletes can be predicted by body fat %. The vertical jump for male is higher than for their female counterparts. Reducing body fat by proper dietary planning will help to improve leg power.
Fulltext Bayesian inference of the Weibull model based on interval-censored survival data

Guure CB, Ibrahim NA, Adam MB

Comput Math Methods Med, 2013;2013:849520.
PMID: 23476718 DOI: 10.1155/2013/849520

Interval-censored data consist of adjacent inspection times that surround an unknown failure time. We have in this paper reviewed the classical approach which is maximum likelihood in estimating the Weibull parameters with interval-censored data. We have also considered the Bayesian approach in estimating the Weibull parameters with interval-censored data under three loss functions. This study became necessary because of the limited discussion in the literature, if at all, with regard to estimating the Weibull parameters with interval-censored data using Bayesian. A simulation study is carried out to compare the performances of the methods. A real data application is also illustrated. It has been observed from the study that the Bayesian estimator is preferred to the classical maximum likelihood estimator for both the scale and shape parameters.
Fulltext Impact of Physical Activity on Cognitive Decline, Dementia, and Its Subtypes: Meta-Analysis of Prospective Studies

Guure CB, Ibrahim NA, Adam MB, Said SM

Biomed Res Int, 2017;2017:9016924.
PMID: 28271072 DOI: 10.1155/2017/9016924

The association of physical activity with dementia and its subtypes has remained controversial in the literature and has continued to be a subject of debate among researchers. A systematic review and meta-analysis of longitudinal studies on the relationship between physical activity and the risk of cognitive decline, all-cause dementia, Alzheimer's disease, and vascular dementia among nondemented subjects are considered. A comprehensive literature search in all available databases was conducted up until April 2016. Well-defined inclusion and exclusion criteria were developed with focus on prospective studies ≥ 12 months. The overall sample from all studies is 117410 with the highest follow-up of 28 years. The analyses are performed with both Bayesian parametric and nonparametric models. Our analysis reveals a protective effect for high physical activity on all-cause dementia, odds ratio of 0.79, 95% CI (0.69, 0.88), a higher and better protective effect for Alzheimer's disease, odds ratio of 0.62, 95% CI (0.49, 0.75), cognitive decline odds ratio of 0.67, 95% CI (0.55, 0.78), and a nonprotective effect for vascular dementia of 0.92, 95% CI (0.62, 1.30). Our findings suggest that physical activity is more protective against Alzheimer's disease than it is for all-cause dementia, vascular dementia, and cognitive decline.
Transformational leadership, empowerment, and job satisfaction: the mediating role of employee empowerment

Choi SL, Goh CF, Adam MB, Tan OK

Hum Resour Health, 2016 Dec 01;14(1):73.
PMID: 27903294

BACKGROUND: Recent studies have revealed that nursing staff turnover remains a major problem in emerging economies. In particular, nursing staff turnover in Malaysia remains high due to a lack of job satisfaction. Despite a shortage of healthcare staff, the Malaysian government plans to create 181 000 new healthcare jobs by 2020 through the Economic Transformation Programme (ETP). This study investigated the causal relationships among perceived transformational leadership, empowerment, and job satisfaction among nurses and medical assistants in two selected large private and public hospitals in Malaysia. This study also explored the mediating effect of empowerment between transformational leadership and job satisfaction.
METHODS: This study used a survey to collect data from 200 nursing staff, i.e., nurses and medical assistants, employed by a large private hospital and a public hospital in Malaysia. Respondents were asked to answer 5-point Likert scale questions regarding transformational leadership, employee empowerment, and job satisfaction. Partial least squares-structural equation modeling (PLS-SEM) was used to analyze the measurement models and to estimate parameters in a path model. Statistical analysis was performed to examine whether empowerment mediated the relationship between transformational leadership and job satisfaction.
RESULTS: This analysis showed that empowerment mediated the effect of transformational leadership on the job satisfaction in nursing staff. Employee empowerment not only is indispensable for enhancing job satisfaction but also mediates the relationship between transformational leadership and job satisfaction among nursing staff.
CONCLUSIONS: The results of this research contribute to the literature on job satisfaction in healthcare industries by enhancing the understanding of the influences of empowerment and transformational leadership on job satisfaction among nursing staff. This study offers important policy insight for healthcare managers who seek to increase job satisfaction among their nursing staff.
Fulltext Joint modelling of longitudinal 3MS scores and the risk of mortality among cognitively impaired individuals

Guure CB, Ibrahim NA, Adam MB, Said SM

PLoS One, 2017;12(8):e0182873.
PMID: 28813458 DOI: 10.1371/journal.pone.0182873

BACKGROUND: Modified Mini-Mental State Examination (3MS) is an instrument administered by trained personnel to examine levels of participants' cognitive function. However, the association between changes in scores over time and the risk of death (mortality) is not known. The aims of this study are to examine the association between 3MS scores and mortality via cognitive impairment among older women and to determine individuals' risk of changes in scores to better predict their survival and mortality rates.
METHODS: We propose a Bayesian joint modelling approach to determine mortality due to cognitive impairment via repeated measures of 3MS scores trajectories over a 21-year follow-up period. Data for this study are taken from the Osteoporotic Fracture longitudinal study among women aged 65+ which started in 1986-88.
RESULTS: The standard relative risk model from the analyses with a baseline 3MS score after adjusting for all the significant covariates demonstrates that, every unit decrease in a 3MS score corresponds to a non-significant 1.059 increase risk of mortality with a 95% CI of (0.981, 1.143), while the extended model results in a significant 0.09% increased risk in mortality. The joint modelling approach found a strong association between the 3MS scores and the risk of mortality, such that, every unit decrease in 3MS scores results in a 1.135 (13%) increased risk of death via cognitive impairment with a 95% CI of (1.056, 1.215).
CONCLUSION: It has been demonstrated that a decrease in 3MS results has a significant increase risk of mortality due to cognitive impairment via joint modelling, but insignificant when considered under the standard relative risk approach.
Improving Gastric Cancer Outcome Prediction Using Single Time-Point Artificial Neural Network Models

Nilsaz-Dezfouli H, Abu-Bakar MR, Arasan J, Adam MB, Pourhoseingholi MA

Cancer Inform, 2017;16:1176935116686062.
PMID: 28469384 DOI: 10.1177/1176935116686062

In cancer studies, the prediction of cancer outcome based on a set of prognostic variables has been a long-standing topic of interest. Current statistical methods for survival analysis offer the possibility of modelling cancer survivability but require unrealistic assumptions about the survival time distribution or proportionality of hazard. Therefore, attention must be paid in developing nonlinear models with less restrictive assumptions. Artificial neural network (ANN) models are primarily useful in prediction when nonlinear approaches are required to sift through the plethora of available information. The applications of ANN models for prognostic and diagnostic classification in medicine have attracted a lot of interest. The applications of ANN models in modelling the survival of patients with gastric cancer have been discussed in some studies without completely considering the censored data. This study proposes an ANN model for predicting gastric cancer survivability, considering the censored data. Five separate single time-point ANN models were developed to predict the outcome of patients after 1, 2, 3, 4, and 5 years. The performance of ANN model in predicting the probabilities of death is consistently high for all time points according to the accuracy and the area under the receiver operating characteristic curve.
Fulltext Mathematical epidemiologic and simulation modelling of first wave COVID-19 in Malaysia

Ariffin MRK, Gopal K, Krishnarajah I, Che Ilias IS, Adam MB, Arasan J, et al.

Sci Rep, 2021 Oct 20;11(1):20739.
PMID: 34671103 DOI: 10.1038/s41598-021-99541-0

Since the first coronavirus disease 2019 (COVID-19) outbreak appeared in Wuhan, mainland China on December 31, 2019, the geographical spread of the epidemic was swift. Malaysia is one of the countries that were hit substantially by the outbreak, particularly in the second wave. This study aims to simulate the infectious trend and trajectory of COVID-19 to understand the severity of the disease and determine the approximate number of days required for the trend to decline. The number of confirmed positive infectious cases [as reported by Ministry of Health, Malaysia (MOH)] were used from January 25, 2020 to March 31, 2020. This study simulated the infectious count for the same duration to assess the predictive capability of the Susceptible-Infectious-Recovered (SIR) model. The same model was used to project the simulation trajectory of confirmed positive infectious cases for 80 days from the beginning of the outbreak and extended the trajectory for another 30 days to obtain an overall picture of the severity of the disease in Malaysia. The transmission rate, β also been utilized to predict the cumulative number of infectious individuals. Using the SIR model, the simulated infectious cases count obtained was not far from the actual count. The simulated trend was able to mimic the actual count and capture the actual spikes approximately. The infectious trajectory simulation for 80 days and the extended trajectory for 110 days depicts that the inclining trend has peaked and ended and will decline towards late April 2020. Furthermore, the predicted cumulative number of infectious individuals tallies with the preparations undertaken by the MOH. The simulation indicates the severity of COVID-19 disease in Malaysia, suggesting a peak of infectiousness in mid-March 2020 and a probable decline in late April 2020. Overall, the study findings indicate that outbreak control measures such as the Movement Control Order (MCO), social distancing and increased hygienic awareness is needed to control the transmission of the outbreak in Malaysia.